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Principles of Experimental Research

ISBN-10: 0750679263

ISBN-13: 9780750679268

Edition: 2006

Authors: K Srinagesh

List price: $73.95
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The need to understand how to design & set up an investigative experiment is nearly universal to all students in engineering, applied technology & science, as well as many of the social sciences. This book offers an introduction to the useful tools needed, including an understanding of logical processes, how to use measurement, & more.
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Book details

List price: $73.95
Copyright year: 2006
Publisher: Elsevier Science & Technology Books
Publication date: 1/9/2006
Binding: Hardcover
Pages: 432
Size: 6.00" wide x 9.00" long x 1.00" tall
Weight: 1.496
Language: English

Experimental Research in Science: Its Name and Nature
Defining Science
Science: Play or Profession?
Science and Research
Varieties of Experimental Research
Conventional Researchers
The Fundamentals
The Importance of Definitions
Toward Definition
Defining "Definition"
Common Terms Used in Definitions
Varieties of Definitions
Need for Definitions
What Definitions Should and Should Not Do
Aspects of Quantification
Quantity and Quality
The Uses of Numbers
An Intellectual Close-up of Counting
The Process of Measurement
Quantities and Measurements
Derived Quantities
Units for Measurement
Fundamental Quantities and Dimensions
Dimensional Analysis
Accuracy versus Approximation
The Purpose and Principles Involved in Experimenting
The Purpose of Experimenting
Cause and Effect
Pertinence and Forms of Cause
Mill's Methods of Experimental Inquiry
Planning for the Experiment
Standardization of Test Material(s)
Number of "Experiments"
Planning the Experiments
Defining the Problem for Experimental Research
To Define a Problem
Relation of the Problem to Resources
Relevance of the Problem
Extent of the Problem
Problem: Qualitative or Quantitative?
Can the Problem Be Reshaped?
Proverbs on Problems
Stating the Problem as a Hypothesis
The Place of Hypothesis in Research
Desirable Qualities of Hypotheses
Designing Experiments to Suit Problems
Several Problems, Several Causes
Treatment Structures
Many Factors at Many Levels, but One Factor at a Time
Factorial Design, the Right Way
Too Many Factors on Hand?
"Subjects-and-Controls" Experiments
Combined Effect of Many Causes
Unavoidable ("Nuisance") Factors
Dealing with Factors
Designing Factors
Experiments with Designed Factors
Matrix of Factors
Remarks on Experiments with Two-Level Factors
Response of Multifactor Experiments
Experiments with More Factors, Each at Two Levels
Fractional Factorials
Varieties of Factors
Levels of Factors
Factors at More Than Two Levels
Limitations of Experiments with Factors at Two Levels
Four-Level Factorial Experiments
Main Effects
More on Interactions
More Factors at More Than Two Levels
The Craft Part of Experimental Research
Searching through Published Literature
Researcher and Scholar
Literature in Print
After the Climb
Building the Experimental Setup
Diversity to Match the Need
Designing the Apparatus
Simplicity, Compactness, and Elegance
Measuring Instruments
Researcher as Handyman
Cost Considerations
The Art of Reasoning in Scientific Research
Logic and Scientific Research
The Subject, Logic
Some Terms in Logic
Induction versus Deduction
Inferential Logic for Experimental Research
Inferential Logic and Experimental Research
Logical Fallacies
Categorical Propositions
Conventions, Symbolism, and Relations among Categorical Propositions
Diagrammatic Representation of Categorical Propositions
Categorical Syllogisms
Ordinary Language and Arguments
Use of Symbolic Logic
The Need for Symbolic Logic
Symbols in Place of Words
Truth Tables
Conditional Statements
Material Implication
Punctuation in Symbolic Logic
Equivalence: "Material" and "Logical"
Application of Symbolic Logic
Validity of Arguments
Probability and Statistics for Experimental Research
Introduction to Probability and Statistics
Relevance of Probability and Statistics in Experimental Research
Defining the Terms: Probability and Statistics
Relation between Probability and Statistics
Philosophy of Probability
Logic of Probability and Statistics
Quantitative Probability
Nature of Statistics
Measures of Central Tendency (Average)
Measures of Dispersion
Tabular Presentations of Statistical Data
Grouping the Data
Graphical Presentations of Data
Normal Distribution Curve
Frequency Distributions That Are Not Normal
Randomization, Replication, and Sampling
Need for Randomization
Applications of Randomization
Methods of Randomization
Meaning of Randomization
Samples and Sampling
Notions of Set
Permutations and Combinations
Quantitative Statement of Randomization
Sampling Methods
Further Significance of Samples
Inference from Samples
Theoretical Sampling Distribution of X
Central Limit Theorem
Standard Normal Distribution
Frequency Distribution and Probability Function
Standard Normal Curve
Questions/Answers Using the APSND Table
Planning the Experiments in Statistical Terms
Guiding Principles
Some Preliminaries for Planned Experiments
Null and Alternate Hypotheses
Accepting (or Rejecting) Hypotheses: Objective Criteria
Procedures for Planning the Experiments
Other Situation Sets
Operating Characteristic Curve
Sequential Experimenting
Concluding Remarks on the Procedures
Statistical Inference from Experimental Data
The Way to Inference
Estimation (From Sample Mean to Population Mean)
Testing of Hypothesis
Regression and Correlation
Multiple Regression